The acquisition of language is essential for normal functioning, and problems with language acquisition can severely limit an individual's educational, career, and social opportunities. One mechanism thought to play a critical role in language acquisition is statistical learning, which refers to the process of extracting subtle patterns from environmental input. Although it is commonly assumed that statistical learning operates implicitly, without requiring conscious effort or awareness, this fundamental assumption has not been directly tested. It is possible that inducing statistical learning to occur explicitly rather than implicitly may engage additional explicit memory systems and may also facilitate sleep-dependent consolidation processes that are critical for long-term retention. The goal of the proposed research is to assess whether and how learning mode alters the memory systems and sleep-dependent consolidation processes that support statistical learning. In the first proposed study, the effect of learning mode on the memory systems recruited for statistical learning will be evaluated, using a combination of behavioral and functional magnetic resonance imaging (fMRI) analyses. In the second proposed study, the effect of learning mode on sleep-dependent consolidation of statistical representations will be assessed, using a combination of behavioral and electroencephalography (EEG) analyses. Because patients often show dissociations of implicit and explicit memory, understanding how learning mode may modulate the memory systems and subsequent sleep-dependent consolidation processes that underlie statistical learning could have tremendous potential to inform treatments for language disorders. For example, by manipulating learning mode, therapies may be developed to selectively target one memory system in order to compensate for dysfunctions in the other, or to promote sleep-dependent consolidation. The proposed fellowship training will provide instruction in two main methodological areas: (1) sleep neurobiology and (2) fMRI analyses. Training in these two different areas will be integrated by the common goal of understanding how learning mode alters the memory systems and consolidation processes that support statistical learning.